期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 33, 期 11, 页码 6545-6557出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2021.3082407
关键词
Trajectory tracking; Artificial neural networks; Trajectory; Vehicle dynamics; Backstepping; Mathematical model; Damping; Additional term; prescribed performance function; robust adaptive control; single unknown parameter; underactuated autonomous underwater vehicles
类别
资金
- National Natural Science Foundation of China [51079013]
- Dalian Science and Technology Innovation Fund Program [2020JJ26GX020]
- Postgraduate Innovation Talent Training Project [CXXM2019BS003]
A novel robust adaptive neural network control scheme is developed for the 3-D trajectory tracking of underactuated autonomous underwater vehicles with uncertain dynamics and unknown disturbances. By introducing new prescribed performance functions and an additional term, the control scheme successfully handles the underactuation problem of AUVs and ensures the stability of the closed-loop control system. Simulation results demonstrate the effectiveness and superiority of the developed control scheme.
A novel robust adaptive neural network (NN) control scheme with prescribed performance is developed for the 3-D trajectory tracking of underactuated autonomous underwater vehicles (AUVs) with uncertain dynamics and unknown disturbances using new prescribed performance functions, an additional term, the radial basis function (RBF) NN, and the command-filtered backstepping approach. Different from the traditional prescribed performance functions, the new prescribed performance functions are innovatively proposed such that the time desired for the trajectory tracking errors of AUVs to reach and stay within the prescribed error tolerance band can be preset exactly and flexibly. The additional term with the Nussbaum function is designed to deal with the underactuation problem of AUVs. By means of RBF NN, the uncertain item lumped by the uncertain dynamics of AUVs and unknown disturbances is eventually transformed into a linearly parametric form with only a single unknown parameter. The developed control scheme ensures that all signals in the AUV 3-D trajectory tracking closed-loop control system are bounded. Simulation results with comparisons show the validity and the superiority of our developed control scheme.
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